PyG Documentation — pytorch_geometric documentation PyG (PyTorch Geometric) is a library built upon PyTorch to easily write and train Graph Neural Networks (GNNs) for a wide range of applications related to structured data
[2507. 16991] PyG 2. 0: Scalable Learning on Real World Graphs In this paper, we present Pyg 2 0 (and its subsequent minor versions), a comprehensive update that introduces substantial improvements in scalability and real-world application capabilities
PyG Overview - NVIDIA Docs PyG (PyTorch Geometric) is a library built upon PyTorch to easily write and train Graph Neural Networks (GNNs) for a wide range of applications related to structured data
pyg-team pytorch_geometric - GitHub PyG (PyTorch Geometric) is a library built upon PyTorch to easily write and train Graph Neural Networks (GNNs) for a wide range of applications related to structured data
torch-geometric · PyPI PyG (PyTorch Geometric) is a library built upon PyTorch to easily write and train Graph Neural Networks (GNNs) for a wide range of applications related to structured data
Installation — pytorch_geometric documentation NVIDIA currently recommends the NVIDIA PyG Container on NGC as the most reliable way to use cuGraph integration with PyG For other installation methods, refer to the cuGraph GNN repository and or the RAPIDS installation guide
pyg-nightly · PyPI PyG (PyTorch Geometric) is a library built upon PyTorch to easily write and train Graph Neural Networks (GNNs) for a wide range of applications related to structured data
Introduction by Example — pytorch_geometric documentation We shortly introduce the fundamental concepts of PyG through self-contained examples For an introduction to Graph Machine Learning, we refer the interested reader to the Stanford CS224W: Machine Learning with Graphs lectures